Multiagent model for agile context inference based on articial immune systems and sparse distributed representations

Abstract

The ubiquity of sensor infrastructures in urban environments poses new challenges in managing the vast amount of data being generated and even more importantly, deriving insights that are relevant and actionable to its users and stakeholders. We argue that understanding the context in which people and things are connected and interacting is of key importance to this end. In this position paper, we present ongoing work in the design of a multiagent model based on immunity theory concepts with the scope of enhancing sensor-driven architectures with context-aware capabilities. We aim to demonstrate our approach in a real-world scenario for processing streams of sensor data in a smart building.